R/rmGeoIdentity.R

In ClimMobTools: API Client for the 'ClimMob' Platform

#' Remove geographical identity
#' 
#' Build a buffer around the a set of geographical coordinates 
#'  and take a random point around the buffer. The function is 
#'  used to omit the precise location of tricot participants 
#'  but keeping a close distance to its agro-environment
#'   
#' @param longlat a data.frame or matrix with geographical coordinates long lat
#' @param dist numeric, buffer distance for all \var{lonlat}
#' @param nQuadSegs integer, number of segments per quadrant
#' @param ... further arguments passed to \code{\link[sf]{sf}} methods
#' @return A data frame with the random coordinates long lat whithin a pre-defined buffer
#' @examplesIf interactive()
#' xy <- matrix(c(11.097799, 60.801090,
#'                11.161298, 60.804199,
#'                11.254428, 60.822457),
#'              nrow = 3, ncol = 2, byrow = TRUE)
#' 
#' rmGeoIdentity(xy)
#' 
#' #' the function also handles NAs
#' 
#' xy2 <- matrix(c(11.097799, 60.801090,
#'                 NA, NA,
#'                 11.161298, 60.804199,
#'                 11.254428, 60.822457,
#'                 11.254428, NA),
#'               nrow = 5, ncol = 2, byrow = TRUE)
#' 
#' rmGeoIdentity(xy2)
#' 
#' @export
rmGeoIdentity <- function(longlat, dist = 0.015, nQuadSegs = 2L, ...){

  longlat <- as.matrix(longlat)

  n <- nrow(longlat)

  # check NAs in lonlat
  anyNAs <- is.na(longlat[,1]) | is.na(longlat[,2])

  # put all both xy as NA
  longlat[anyNAs, ] <- NA

  # split lonlat by rows
  longlat <- split(longlat, seq_len(n))

  # transform into sf points
  longlat <- lapply(longlat, function(l) {
    a <- list(x = l)
    do.call("st_point", a)
  })

  # and then into a geometry list column
  longlat <- do.call("st_sfc", longlat)

  args <- list(x = longlat,
               dist = dist, 
               nQuadSegs = nQuadSegs)
  
  lonlatb <- do.call("st_buffer", args)
  
  result <- split(lonlatb, seq_len(n))

  result[!anyNAs] <- lapply(result[!anyNAs], function(x){
    a <- list(x = x, size = 1, type = "random", by_polygon = TRUE)
    do.call("st_sample", a)
  })

  result <- do.call(rbind, result)

  result <- do.call("st_sfc", result)

  r <- matrix(NA, nrow = n, ncol = 2)

  r[!anyNAs, ] <- matrix(unlist(result),
                         ncol = 2,
                         nrow = sum(!anyNAs),
                         byrow = TRUE)

  r <- as.data.frame(r)

  names(r) <- c("long", "lat")

  return(r)

}